| Proj No. | A1101-251 |
| Title | Calibration of LiDAR and Camera Sensors |
| Summary | Accurate calibration of LiDAR and camera sensors is essential for fusing multimodal sensor data in autonomous systems. Proper calibration ensures precise alignment between depth and visual information, enhancing perception tasks such as object detection, semantic segmentation, and 3D reconstruction. However, existing calibration techniques often require controlled environments and specialized calibration targets, limiting their practicality in dynamic real-world settings. This project aims to develop an efficient and robust calibration method for LiDAR-camera systems that works in both structured and unstructured environments. Students will investigate geometric and photometric calibration techniques, including feature-based and optimization-based approaches, to align point clouds with image data. The research will involve both simulation and real-world experiments, using hardware provided by the EEE IoT Lab. The final objective is to contribute novel insights into LiDAR-camera calibration. The student candidates should possess the following qualities: • Strong understanding of coordinate transformations and projection models. • Proficiency in C++ or Python programming. • Experience with ROS. • Familiarity with point cloud processing techniques. • A commitment to conducting experimental work. |
| Supervisor | Prof Xie Lihua (Loc:S2 > S2 B2C > S2 B2C 94, Ext: +65 67904524) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Internet of Things Laboratory (Loc: S1-B4c-14, ext: 5470/5475) |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: |